基于SIRS模型的高校科研团队内部隐性知识传播模型  

Tacit Knowledge Dissemination Model within University Research Team Based on SIRS Model

作　　者：王超[1] 倪静[1] WANG Chao;NI Jing(Business School,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学管理学院,上海200093

出　　处：《科技和产业》2021年第10期234-238,共5页Science Technology and Industry

基　　金：教育部人文社科基金(19YJAZH064)。

摘　　要：在高校科研团队内隐性知识传播在研究生的培养过程中扮演着重要的角色,因此研究隐性知识在高校科研团队内部的传播机制和影响因素尤为重要。针对以往隐性知识传播考虑因素不全面以及遗忘率设置为常数的问题,首先阐述团队录取率、流出率、再学习率和Ebbinghaus遗忘函数对隐性知识传播的影响,接着构建包含隐性知识未持有者、隐性知识持有者以及隐性知识免疫者在内的SIRS传播模型,列出隐性知识传播的微分动力学方程;最后,利用MATLAB对模型进行仿真研究。结果表明:低录取率和高流出率不利于团队内部隐性知识持有者人数的稳定,而过高的录取率会使团队内的隐性知识持有者的人数达到最大值;随时间变化的Ebbinghaus遗忘函数会影响隐性知识持有者的人数,一般在4~5 d后隐性知识持有者遗忘知识;再学习率的改变对隐性知识免疫者的影响最明显。Tacit knowledge plays an important role in scientific research teams in colleges and universities.Therefore,it is particularly important to study the dissemination mechanis-m and influencing factors of tacit knowledge within scientific research teams.Firstly,the SIRS model of three spreading subjects including tacit knowledge non-holder,tacit knowledge holder and tacit knowledge immuner is constructed,and the differential dynamics equation of tacit knowledge dissemination is constructed.Then,the effects of team acceptance rate,turnover rate,relearning rate and Ebbinghaus forgetting function on tacit knowledge transmission are considered respectively.Finally,MATLAB is used to simulate the parameters of the model.The numerical results show that low acceptance rate and high turnover rate are not conducive to the stability of the number of tacit knowledge holders within the team,while high acceptance rate will reach a maximum number of tacit knowledge holders within the team.The Ebbinghaus forgetting function changes with time will affect the number of tacit knowledge holders,and tacit knowledge holders generally forget knowledge after 4~5 days.The change of relearning rate has the most obvious influence on tacit knowledge immuner.

关 键 词：高校科研团队 隐性知识传播 Ebbinghaus遗忘曲线 SIRS模型 

分 类 号：F204[经济管理—国民经济] N949[自然科学总论—系统科学]